Enseigné par

Google Cloud Training

Transcription

Hello. I'm Diane Greene, and I lead Google Cloud. I'd like to welcome you to our deep dive course on Practical Machine Learning using Google Cloud Platform. We've had thousands of Google engineers go through different variations of this course and have also shared it with several of our customers. Through this course, we've enabled Python programmers to do machine learning, and data scientists to build production-ready machine learning models. This was only possible because we're using Google's incredible infrastructure and ML platform. One of our large global customers told us that switching to GCP, Google Cloud Platform, had helped them reduce organizational silos. This was because of the combination of global serverless infrastructure like BigQuery and open source software like TensorFlow, which democratized access to data and machine learning across their organization. In this Coursera specialization, you'll learn the key technical skills to replicate this and drive transformation across your company. I'm very excited to invite you to take this course and start training, deploying, and serving Machine Learning models on Google Cloud. Thank you. Thanks, Diane. I'm Valliappa Lakshmanan. Everyone calls me Lak. I'm a Technical Lead for Big Data and Machine Learning professional services at Google Cloud. I lead the team that wrote this machine learning course for you and I'll be teaching parts of the course as well. You'll see many of my co-authors throughout the series. As Diane said, the aim of this specialization is to give you a practical real-world introduction to machine learning. The goal is to enable you, whether you're a Python programmer, data engineer or a data scientist, to do machine learning and to build production machine learning models. So what will you learn?